Yin Jian, Fenley Andrew T, Henriksen Niel M, Gilson Michael K
Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California 92093-0736, United States.
J Phys Chem B. 2015 Aug 13;119(32):10145-55. doi: 10.1021/acs.jpcb.5b04262. Epub 2015 Aug 5.
Improving the capability of atomistic computer models to predict the thermodynamics of noncovalent binding is critical for successful structure-based drug design, and the accuracy of such calculations remains limited by nonoptimal force field parameters. Ideally, one would incorporate protein-ligand affinity data into force field parametrization, but this would be inefficient and costly. We now demonstrate that sensitivity analysis can be used to efficiently tune Lennard-Jones parameters of aqueous host-guest systems for increasingly accurate calculations of binding enthalpy. These results highlight the promise of a comprehensive use of calorimetric host-guest binding data, along with existing validation data sets, to improve force field parameters for the simulation of noncovalent binding, with the ultimate goal of making protein-ligand modeling more accurate and hence speeding drug discovery.
提高原子计算机模型预测非共价结合热力学的能力对于基于结构的药物设计的成功至关重要,而此类计算的准确性仍然受到非最优力场参数的限制。理想情况下,人们会将蛋白质-配体亲和力数据纳入力场参数化,但这将效率低下且成本高昂。我们现在证明,敏感性分析可用于有效地调整水相主体-客体系统的 Lennard-Jones 参数,以更准确地计算结合焓。这些结果凸显了全面利用量热法主体-客体结合数据以及现有验证数据集来改进用于模拟非共价结合的力场参数的前景,其最终目标是使蛋白质-配体建模更加准确,从而加速药物发现。